The geriatric population in the United States is the most rapidly expanding age group with individuals over age of 65 comprising approximately 12% of the US population. End stage renal disease (ESRD) is a major health problem in this population with an incidence that has been steadily increasing over the last 10 years. More than 70% of ESRD in this population is associated with either diabetes mellitus and/or hypertension. The remaining 30% can be ascribed to other causes, including glomerulonephritis. Numerous studies have suggested that genetic predisposition to diabetic nephropathy, but genes for nephropathy have not yet been identified. We and others have hypothesized that ESRD is a complex disease with multiple genes and environment potentially contributing to its etiology. Because of the complexity of ESRD, identification of genes for this disease may prove difficult. Lessons learned from genetic research in other complex diseases such as diabetes, hypertension, asthma and obesity indicate that a concerted effort to establish a standardized collection of clinically well-defined families will prove beneficial in the discovery of ESRD genes. We propose to form a Genotyping and Data Coordinating Center (GADCC) for ESRD that will enable six different participating centers (PICs) to collect data from ESRD clinical populations ascertained through well-defined inclusion and exclusion criteria. To achieve this goal we will: (1) Establish an ESRD consortium, comprised of members from six PICs, with oversight by members from the National Institute of Digestive and Kidney Disease, and the External Advisory Committee, (2) Construct a state-of-the-art database for management of data across all six institutions, (3) Provide molecular and statistical genetic expertise and resources to the members of the consortium to map genes for nephropathy. Our overall goal is to establish a network of investigators, with well-characterized clinical populations, who will facilitate mapping of genes for ESRD in a timely manner using novel molecular and statistical genetic technologies.